Actuator and sensor fault detection and diagnosis of quadrotor based on Two-Stage Kalman Filter

Majid Moghadam; Fikret Caliskan

Actuator and sensor fault detection and diagnosis of quadrotor based on Two-Stage Kalman Filter

Majid Moghadam, Fikret Caliskan

Department of Control and Automation Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

20 Citations (Scopus)

Abstract

This paper addresses the problem of sensor and actuator fault detection and diagnosis (FDD) of an unmanned quadrotor helicopter in the presence of the observation and process noises. To this end a Two-Stage Kalman Filter (TSKF) to detect, isolate and identify faults is used. Sensor faults are assumed to be bias faults and actuator faults are modeled as a loss of effectiveness in the propellers. Also a discrete-time Linear Quadratic Regulator (LQR) controller is used to make the system response to follow a desired trajectory.

Original language	English
Title of host publication	2015 Australian Control Conference, AUCC 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	182-187
Number of pages	6
ISBN (Electronic)	9781922107695
Publication status	Published - 21 Dec 2015
Event	5th Australian Control Conference, AUCC 2015 - Gold Coast, Australia Duration: 5 Nov 2015 → 6 Nov 2015

Publication series

Name	2015 Australian Control Conference, AUCC 2015

Conference

Conference	5th Australian Control Conference, AUCC 2015
Country/Territory	Australia
City	Gold Coast
Period	5/11/15 → 6/11/15

Bibliographical note

Publisher Copyright:
© 2015 Engineers Australia.

Cite this

@inproceedings{5bf789addb894cc7ac82659f8fa2995e,

title = "Actuator and sensor fault detection and diagnosis of quadrotor based on Two-Stage Kalman Filter",

abstract = "This paper addresses the problem of sensor and actuator fault detection and diagnosis (FDD) of an unmanned quadrotor helicopter in the presence of the observation and process noises. To this end a Two-Stage Kalman Filter (TSKF) to detect, isolate and identify faults is used. Sensor faults are assumed to be bias faults and actuator faults are modeled as a loss of effectiveness in the propellers. Also a discrete-time Linear Quadratic Regulator (LQR) controller is used to make the system response to follow a desired trajectory.",

author = "Majid Moghadam and Fikret Caliskan",

note = "Publisher Copyright: {\textcopyright} 2015 Engineers Australia.; 5th Australian Control Conference, AUCC 2015 ; Conference date: 05-11-2015 Through 06-11-2015",

year = "2015",

month = dec,

day = "21",

language = "English",

series = "2015 Australian Control Conference, AUCC 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "182--187",

booktitle = "2015 Australian Control Conference, AUCC 2015",

address = "United States",

}

Moghadam, M & Caliskan, F 2015, Actuator and sensor fault detection and diagnosis of quadrotor based on Two-Stage Kalman Filter. in 2015 Australian Control Conference, AUCC 2015., 7361930, 2015 Australian Control Conference, AUCC 2015, Institute of Electrical and Electronics Engineers Inc., pp. 182-187, 5th Australian Control Conference, AUCC 2015, Gold Coast, Australia, 5/11/15.

Actuator and sensor fault detection and diagnosis of quadrotor based on Two-Stage Kalman Filter. / Moghadam, Majid; Caliskan, Fikret.
2015 Australian Control Conference, AUCC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 182-187 7361930 (2015 Australian Control Conference, AUCC 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Actuator and sensor fault detection and diagnosis of quadrotor based on Two-Stage Kalman Filter

AU - Moghadam, Majid

AU - Caliskan, Fikret

PY - 2015/12/21

Y1 - 2015/12/21

N2 - This paper addresses the problem of sensor and actuator fault detection and diagnosis (FDD) of an unmanned quadrotor helicopter in the presence of the observation and process noises. To this end a Two-Stage Kalman Filter (TSKF) to detect, isolate and identify faults is used. Sensor faults are assumed to be bias faults and actuator faults are modeled as a loss of effectiveness in the propellers. Also a discrete-time Linear Quadratic Regulator (LQR) controller is used to make the system response to follow a desired trajectory.

AB - This paper addresses the problem of sensor and actuator fault detection and diagnosis (FDD) of an unmanned quadrotor helicopter in the presence of the observation and process noises. To this end a Two-Stage Kalman Filter (TSKF) to detect, isolate and identify faults is used. Sensor faults are assumed to be bias faults and actuator faults are modeled as a loss of effectiveness in the propellers. Also a discrete-time Linear Quadratic Regulator (LQR) controller is used to make the system response to follow a desired trajectory.

UR - http://www.scopus.com/inward/record.url?scp=84964012134&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84964012134

T3 - 2015 Australian Control Conference, AUCC 2015

SP - 182

EP - 187

BT - 2015 Australian Control Conference, AUCC 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th Australian Control Conference, AUCC 2015

Y2 - 5 November 2015 through 6 November 2015

ER -

Actuator and sensor fault detection and diagnosis of quadrotor based on Two-Stage Kalman Filter

Abstract

Publication series

Conference

Bibliographical note

Other files and links

Fingerprint

Cite this